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Abdul Aziz
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INDONESIA
The Eastasouth Journal of Information System and Computer Science
Published by Eastasouth Institute
ISSN : 30266041     EISSN : 3025566X     DOI : https://doi.org/10.58812/esiscs
Core Subject : Science,
ESISCS - The Eastasouth Journal of Information System and Computer Science is a peer-reviewed journal and open access three times a year (April, August, December) published by Eastasouth Institute. ESISCS aims to publish articles in the field of Enterprise systems and applications, Database management systems, Decision support systems, Knowledge management systems, E-commerce and e-business systems, Business intelligence and analytics, Information system security and privacy, Human-computer interaction, Algorithms and data structures, Artificial intelligence and machine learning, Computer vision and image processing, Computer networks and communications, Distributed and parallel computing, Software engineering and development, Information retrieval and web mining, Cloud computing and big data. ESISCS accepts manuscripts of both quantitative and qualitative research. ESISCS publishes papers: 1) review papers, 2) basic research papers, and 3) case study papers. ESISCS has been indexed in, Crossref, and others indexing. All submissions should be formatted in accordance with ESISCS template and through Open Journal System (OJS) only.
Articles 11 Documents
Search results for , issue "Vol. 1 No. 01 (2023): The Eastasouth Journal of Information System and Computer Science (ESISCS)" : 11 Documents clear
Building Robust Fintech Reporting Systems Using JPA with Embedded SQL for Real-Time Data Accuracy and Consistency Bayya, Anil Kumar
The Eastasouth Journal of Information System and Computer Science Vol. 1 No. 01 (2023): The Eastasouth Journal of Information System and Computer Science (ESISCS)
Publisher : Eastasouth Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/esiscs.v1i01.480

Abstract

In the rapidly evolving fintech domain, the need for high-throughput, low-latency, real-time reporting systems has increased due to rising transaction volumes. This paper examines the architectural design and technical implementation of fintech reporting systems integrating Java Persistence API (JPA) with embedded SQL, ensuring data accuracy, efficient query execution, and transaction consistency. JPA, an Object-Relational Mapping (ORM) framework, abstracts interactions between Java objects and relational databases, simplifying development through entity mapping and reducing boilerplate code. Annotations like @Entity, @Table, and @Column define entity relationships and constraints, enabling automated schema synchronization. Embedded SQL complements JPA by allowing direct SQL query injection, optimizing complex, performance-critical queries while maintaining JPA’s portability. A multi-tier design ensures separation of concerns and scalability. The persistence layer, managed by JPA, facilitates database interaction, while connection pooling (e.g., HikariCP) and caching strategies (first-level and second-level) enhance transaction throughput. Transactional integrity is enforced via isolation levels, locking strategies, and batch processing, preventing issues like dirty reads and lost updates. Using native SQL queries via JPA’s create Native Query method, the system leverages advanced database optimization features. Profiling tools ensure minimal query latency, supporting real-time financial reporting with strict performance standards. By combining JPA’s abstraction with embedded SQL’s efficiency, this architecture provides a resilient, scalable reporting system, ensuring data integrity and optimized query execution for fintech operations.

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